Optimality in evolution: new insights from synthetic biology

被引:14
|
作者
de Vos, Marjon G. J. [1 ]
Poelwijk, Frank J. [1 ]
Tans, Sander J. [1 ]
机构
[1] FOM Inst AMOLF, NL-1098 XG Amsterdam, Netherlands
关键词
FITNESS PEAKS; LIMITS; COST; ENVIRONMENTS; OPTIMIZATION; ARCHITECTURE; MAINTENANCE; POPULATIONS; LANDSCAPES; EXPRESSION;
D O I
10.1016/j.copbio.2013.04.008
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Whether organisms evolve to perform tasks optimally has intrigued biologists since Lamarck and Darwin. Optimality models have been used to study diverse properties such as shape, locomotion, and behavior. However, without access to the genetic underpinnings or the ability to manipulate biological functions, it has been difficult to understand an organism's intrinsic potential and limitations. Now, novel experiments are overcoming these technical obstacles and have begun to test optimality in more quantitative terms. With the use of simple model systems, genetic engineering, and mathematical modeling, one can independently quantify the prevailing selective pressures and optimal phenotypes. These studies have given an exciting view into the evolutionary potential and constraints of biological systems, and hold the promise to further test the limits of predicting future evolutionary change.
引用
收藏
页码:797 / 802
页数:6
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